.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        Click :ref:`here <sphx_glr_download_auto_examples_datasets_plot_dataset_arithmetic.py>`     to download the full example code
    .. rst-class:: sphx-glr-example-title

    .. _sphx_glr_auto_examples_datasets_plot_dataset_arithmetic.py:


==================
Dataset Arithmetic
==================

This plots example volume data onto an example subject, S1, onto a flatmap
using quickflat. In order for this to run, you have to have a flatmap for
this subject in the pycortex filestore.

Once you have created a cortex.Volume object, you can manipulate it with
normal arithmetic operators like +, -, *, /, and **



.. rst-class:: sphx-glr-horizontal


    *

      .. image:: /auto_examples/datasets/images/sphx_glr_plot_dataset_arithmetic_001.png
          :alt: plot dataset arithmetic
          :class: sphx-glr-multi-img

    *

      .. image:: /auto_examples/datasets/images/sphx_glr_plot_dataset_arithmetic_002.png
          :alt: plot dataset arithmetic
          :class: sphx-glr-multi-img

    *

      .. image:: /auto_examples/datasets/images/sphx_glr_plot_dataset_arithmetic_003.png
          :alt: plot dataset arithmetic
          :class: sphx-glr-multi-img






.. code-block:: default


    import cortex
    import numpy as np
    np.random.seed(1234)
    import matplotlib.pyplot as plt

    subject = 'S1'
    xfm = 'fullhead'

    # Creating a random dataset that is the shape for this transform with one
    # entry for each voxel
    test_data = np.random.randn(31, 100, 100)

    # This creates a Volume object for our test dataset for the given subject
    # and transform
    vol_data = cortex.Volume(test_data, subject, xfm, vmin=-2, vmax=2)
    cortex.quickshow(vol_data)
    plt.show()

    # Now you can do arithmetic with the Volume
    vol_plus = vol_data + 1
    cortex.quickshow(vol_plus)
    plt.show()

    # You can also do multiplication
    vol_mult = vol_data * 4
    cortex.quickshow(vol_mult)
    plt.show()


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** ( 0 minutes  6.903 seconds)


.. _sphx_glr_download_auto_examples_datasets_plot_dataset_arithmetic.py:


.. only :: html

 .. container:: sphx-glr-footer
    :class: sphx-glr-footer-example



  .. container:: sphx-glr-download sphx-glr-download-python

     :download:`Download Python source code: plot_dataset_arithmetic.py <plot_dataset_arithmetic.py>`



  .. container:: sphx-glr-download sphx-glr-download-jupyter

     :download:`Download Jupyter notebook: plot_dataset_arithmetic.ipynb <plot_dataset_arithmetic.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_